Our Faculty

Ramesh Manyam

Assistant Research Professor
Department of Biostatistics and Bioinformatics
PUBLICATIONS
PUBMED

Bio

Dr. Manyam's research focuses on artificial intelligence, data science, large-scale data analytics, machine learning, risk modeling, and software application development. Specific areas of interest include longitudinal electronic health records (EHR) data analytics, time series analyses, and risk prediction using statistical and ML algorithms (e.g., survival regression. decision trees, extreme gradient boosting, XGBoost, random survival forests, support vector machines, reinforcement learning, and neural networks) and development of customized AI-driven education and conversational companions.    
Dr. Manyam is a trained computer scientist with decades of experience in data-driven research studies, building custom databases, software applications, and data visualization portals. He has hands-on experience with large-scale healthcare data sources, such as EPIC’s EHR, Emory clinical data warehouse,and national clinical and surgical databases. Dr. Manyam currently leads the 'Artificial Intelligence and Data Translation' concentration of the Doctor of Public Health (DrPH)  program and researches computationally efficient ML/AI approaches and their applications for better health. 
Dr. Manyam's current research collaborative efforts include, but not limited to: 1) developing scalable, portable and interpretable  ML/AI-powered risk models - via automated feature engineering, feature selection, ensemble learning and deep learning techniques - to accurately evaluate risk factors for outcomes such as, (a) maternal morbidity and mortality, (b) medication safety in older adults with Alzheimer's disease and related dementias, (c) inter-hospital transfer among older adults, (d) early mortality after inter-hospital transfer among older adults, (e) suicidal ideation and behavior,  (f) mortality after surgery for femoral shaft fractures, (g) perioperative blood transfusion in femoral shaft fracture patient cohort, (h) hospital readmission after coronary artery bypass grafting (CABG), and (i) failure-to-rescue after CABG.  

Recent honors and awards

Areas of Interest

  • Data Science
  • High Performance Computing
  • Longitudinal Analysis
  • Machine Learning
  • Risk Assessment
  • Survival Analysis
  • Cardiovascular Diseases
  • Bioinformatics
  • Artificial Intelligence
  • Mental Health
  • Health Informatics
  • Maternal and Child Health

Education

  • PhD, Georgia State University, Atlanta, GA, USA
  • MS, Georgia State University, Atlanta, GA, USA
  • MTech, Indian Institute of Technology, Banaras Hindu University, Varanasi, India
  • BTech, National Institute of Technology, Warangal, India

Courses Taught

  • BIOS 585 - Python Programming
  • DATA 521 - Database Development for PH

Affiliations

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